To protect against data loss, an organization may use a backup system to back up important data. In order to reduce the resources required to store backup images, the organization may store backup images within deduplicating data systems.
Deduplicating data systems are often able to reduce the amount of storage space needed to store files by recognizing redundant data patterns. For example, a conventional deduplicating data system may reduce the amount of storage space needed to store similar files by dividing the files into data segments and storing only unique data segments. In this example, each deduplicated file stored within the deduplicating data system may be represented by a list of references to those data segments that make up the file.
Unfortunately, deduplication operations may involve significant overhead. For example, tracking a large number of small data segments may consume additional storage and may consume more client-side processing resources. Increasing the size of the data segments may reduce overhead, but may also reduce the number of reusable data segments, thereby reducing the overall efficacy of deduplication. Thus, data segments that are too large or that are too small may negatively impact the consumption of computing resources.
Accordingly, the instant disclosure identifies and addresses a need for additional and improved systems and methods for efficient backup deduplication.